The human brain has the extraordinary capability to transform cluttered sensory input into distinct object representations. For example, it is able to rapidly and seemingly without effort detect object categories in complex natural scenes. Surprisingly, category tuning is not sufficient to achieve conscious recognition of objects. What neural process beyond category extraction might elevate neural representations to the level where objects are consciously perceived? Here we show that visible and invisible faces produce similar category-selective responses in the ventral visual cortex. The pattern of neural activity evoked by visible faces could be used to decode the presence of invisible faces and vice versa. However, only visible faces caused extensive response enhancements and changes in neural oscillatory synchronization, as well as increased functional connectivity between higher and lower visual areas. We conclude that conscious face perception is more tightly linked to neural processes of sustained information integration and binding than to processes accommodating face category tuning.

It has become an accepted paradigm that humans have “prosocial preferences” that lead to higher levels of cooperation than those that would maximize their personal financial gain. However, the existence of prosocial preferences has been inferred post hoc from the results of economic games, rather than with direct experimental tests. Here, we test how behavior in a public-goods game is influenced by knowledge of the consequences of actions for other players. We found that (i) individuals cooperate at similar levels, even when they are not informed that their behavior benefits others; (ii) an increased awareness of how cooperation benefits others leads to a reduction, rather than an increase, in the level of cooperation; and (iii) cooperation can be either lower or higher than expected, depending on experimental design. Overall, these results contradict the suggested role of the prosocial preferences hypothesis and show how the complexity of human behavior can lead to misleading conclusions from controlled laboratory experiments.

Older adults are disproportionately vulnerable to fraud, and federal agencies have speculated that excessive trust explains their greater vulnerability. Two studies, one behavioral and one using neuroimaging methodology, identified age differences in trust and their neural underpinnings. Older and younger adults rated faces high in trust cues similarly, but older adults perceived faces with cues to untrustworthiness to be significantly more trustworthy and approachable than younger adults. This age-related pattern was mirrored in neural activation to cues of trustworthiness. Whereas younger adults showed greater anterior insula activation to untrustworthy versus trustworthy faces, older adults showed muted activation of the anterior insula to untrustworthy faces. The insula has been shown to support interoceptive awareness that forms the basis of “gut feelings,” which represent expected risk and predict risk-avoidant behavior. Thus, a diminished “gut” response to cues of untrustworthiness may partially underlie older adults’ vulnerability to fraud.

Sensory-motor behavior results from a complex interaction of noisy sensory data with priors based on recent experience. By varying the stimulus form and contrast for the initiation of smooth pursuit eye movements in monkeys, we show that visual motion inputs compete with two independent priors: one prior biases eye speed toward zero; the other prior attracts eye direction according to the past several days' history of target directions. The priors bias the speed and direction of the initiation of pursuit for the weak sensory data provided by the motion of a low-contrast sine wave grating. However, the priors have relatively little effect on pursuit speed and direction when the visual stimulus arises from the coherent motion of a high-contrast patch of dots. For any given stimulus form, the mean and variance of eye speed covary in the initiation of pursuit, as expected for signal-dependent noise. This relationship suggests that pursuit implements a trade-off between movement accuracy and variation, reducing both when the sensory signals are noisy. The tradeoff is implemented as a competition of sensory data and priors that follows the rules of Bayesian estimation. Computer simulations show that the priors can be understood as direction-specific control of the strength of visual-motor transmission, and can be implemented in a neural-network model that makes testable predictions about the population response in the smooth eye movement region of the frontal eye fields.

The division of human learning systems into reward and punishment opponent modules is still a debated issue. While the implication of ventral prefrontostriatal circuits in reward-based learning is well established, the neural underpinnings of punishment-based learning remain unclear. To elucidate the causal implication of brain regions that were related to punishment learning in a previous functional neuroimaging study, we tested the effects of brain damage on behavioral performance, using the same task contrasting monetary gains and losses. Cortical and subcortical candidate regions, the anterior insula and dorsal striatum, were assessed in patients presenting brain tumor and Huntington disease, respectively. Both groups exhibited selective impairment of punishment-based learning. Computational modeling suggested complementary roles for these structures: the anterior insula might be involved in learning the negative value of loss-predicting cues, whereas the dorsal striatum might be involved in choosing between those cues so as to avoid the worst.